Factors affecting Kaposi’s sarcoma-associated herpesvirus transmission in rural Ugandan households, a longitudinal study

Background We report the impact of HIV infection within a household on oral Kaposi’s sarcoma-associated herpesvirus (KSHV) shedding. Methods We enrolled 469 individuals from 90 households. Mouthwash rinse samples collected at three monthly visits, were analyzed for KSHV DNA using quantitative polymerase chain reaction (qPCR). Generalized linear mixed effects logistic models were applied to analyze factors associated with KSHV ever shedding, and among shedders, always versus intermittent shedding. Linear mixed effects models were applied to models of KSHV viral loads. Intraclass correlation coefficients (ICCs) were calculated to assess the contribution of household-level factors to variations in shedding probabilities. Hotspot analyses of geospatial feature clusters were calculated using Getis-Ord Gi* statistic and visualized using inverse distance weighted interpolation. Results Analyses included 340 KSHV seropositive individuals, aged 3 + years, with qPCR results from 89 households. Forty households had 1 + persons living with HIV (PLWH), while 49 had none. Among participants, 149(44%) were KSHV ever shedders. Of 140 who shed KSHV at two or more visits, 34(24%) were always shedders. Increasing number of KSHV seropositive household members was significantly associated with ever shedding [Odds ratio(OR) (95% Confidence Interval(95%CI)):1.14(1.03,1.26);p = 0.013]. Among KSHV shedders, a statistically significant age-related trend was identified with 10–19 years being more likely to be always shedders (type III test p = 0.039) and to have higher viral loads (type III test p = 0.027). In addition, higher viral loads were significantly associated with increasing number of household members [coefficient(95%CI):0.06(0.01,0.12);p = 0.042], increasing number of KSHV seropositive members [coefficient(95%CI):0.08(0.01,0.15);p = 0.021], and living in households with 1 + PLWH [coefficient(95%CI):0.51(0.04,0.98);p = 0.033]. Always shedders exhibited higher viral loads than intermittent shedders [coefficient(95%CI):1.62(1.19,2.05);p < 0.001], and viral loads increased with the number of visits where KSHV DNA was detected in saliva (type III test p < 0.001). Household-level factors attributed for 19% of the variability in KSHV shedding (ICC:0.191;p = 0.010). Geospatial analysis indicated overlapping hotspots of households with more KSHV seropositive individuals and KSHV shedders, distinct from areas where PLWH were clustered. Discussion KSHV oral shedding is influenced by multiple factors at the individual, household, and regional levels. To mitigate ongoing KSHV transmission a comprehensive understanding of factors contributing to oral KSHV reactivation and transmission within households is needed.


Background
We report the impact of HIV infection within a household on oral Kaposi's sarcoma-associated herpesvirus (KSHV) shedding.

Methods
We enrolled 469 individuals from 90 households.Mouthwash rinse samples collected at three monthly visits, were analyzed for KSHV DNA using quantitative polymerase chain reaction (qPCR).Generalized linear mixed effects logistic models were applied to analyze factors associated with KSHV ever shedding, and among shedders, always versus intermittent shedding.Linear mixed effects models were applied to models of KSHV viral loads.Intraclass correlation coe cients (ICCs) were calculated to assess the contribution of household-level factors to variations in shedding probabilities.Hotspot analyses of geospatial feature clusters were calculated using Getis-Ord Gi* statistic and visualized using inverse distance weighted interpolation.

Discussion
HIV in a rural African population, consists of 22,000 individuals from 25 neighboring villages (18).KSHV seroprevalence in this region is the highest reported at over 90% (21) and HIV prevalence has remained stable at 6-7% (18,19).Regular annual census and bi-annual survey rounds are completed.Within the census GPS coordinates and other census data are obtained from the households.Data on HIV status are obtained from the survey rounds.

Study Design
Between August-October 2021, we enrolled members from 90 households in a longitudinal cohort study.
Households were pre-identi ed using HIV statuses collected from GPC survey data and included 45 households with at least one member living with HIV (PLWH) and 45 households with no members living with HIV.Anyone staying in the home at least 50% of the time was welcome to participate, regardless of age or sex.After enrollment, two follow-up visits at one month apart for a total of three visits were completed.Ethical approval was obtained by the Uganda Virus Research Institute Research Ethics Committee (UVRI-REC), Uganda National Council for Science and Technology (UNCST), and Colorado Multiple Institutional Review Board (COMIRB).All participants provided written/thumb printed informed consent.Parent/guardian consent was obtained for participants aged < 18 years.Assent was obtained from children aged 8-17 years.Procedures were completed in accordance with the ethical standards of the Helsinki Declaration.

Data collected
At each visit a questionnaire was administered by the eld team which collected data on sex, age, and household size.Socioeconomic statuses were derived from variables collected on the characteristics of the household's main house (roof, walls, etc), whether owned by household members, and whether household members owned any building for rent (house, shop, kiosk, etc).Principal components were calculated using the covariance matrix households classi ed into ve quantiles.If individuals had been ill in the last month, they were asked to provide information on clinical symptoms, whether they accessed care, type of care accessed, treatment given for their illness, and nal diagnosis.

HIV determination
At enrollment, data was collected by self-report on each individual's HIV infection status, years since HIV diagnosis, and current anti-retroviral therapy (ART) use, if applicable.For a subset of individuals, we were able to con rm HIV status using previously completed study data.HIV seropositive individuals were those who self-reported as HIV positive or whose HIV status was con rmed using previously collected GPC census or other study data.
All others were considered HIV negative.Household HIV status was reassessed and re-categorized based on identi ed individual HIV status.

Sample processing
Up to 5 ml of venous blood was collected in EDTA tubes for each individual at baseline, 1.5 ml whole blood was removed and stored for subsequent DNA extraction.The remaining blood was centrifuged at 10,000 rpm for 5 minutes at room temperature, and plasma removed and stored for antibody testing.At enrollment and each follow-up study participants rinsed their mouth with 2.5mL Listerine mouthwash.
After collection, up to 2 ml of oral uid was transferred and spun at room temperature at 1500xg for 10 minutes.Supernatant was removed from the cell pellet.The cell pellets were used for subsequent analysis.All blood and oral uid samples were stored at -80 o C until further analysis.
Positive controls included US-based adults with active or history of KSHV-associated disease and/or KSHV DNA detected in peripheral blood mononuclear cells (PBMC).Receiver operating curves or a parametric distribution using negative and positive control sera were used to identify cut-offs (22).Individuals were identi ed as KSHV seropositive if IgG to any of the 25 KSHV antigens were detected in plasma.EBV seropositivity was de ned as detection of anti-EBV IgG antibodies to VCA or EBNA-1.

KSHV shedding
Mouthwash rinse samples were tested for detection of KSHV DNA using qPCR as previously described (23).Brie y, the Qiagen blood mini kit (Qiagen, Valencia, CA) was used to extract DNA from oral uid cell pellets and the DNA was tested using primers speci c to the KSHV K6 gene region and the human endogenous retrovirus 3 (ERV-3) gene which is used for cell quanti cation (24).Samples were run in triplicate in both assays and the average values of the independent reactions calculated.KSHV viral load was reported as copies per million cell equivalents.Individuals were identi ed as KSHV shedders if KSHV DNA was detected in oral uids at any timepoint and non-shedders if not.Among KSHV shedders, we categorized individuals as either always shedders, if KSHV DNA was detected in oral uids in all samples collected, or intermittent shedders, if KSHV DNA was detected at least once but not in all samples.Individuals with only one visit were included in the shedder vs non-shedder analysis but excluded from the analyses of always vs intermittent shedders.KSHV viral loads were log transformed prior to analyses.

Statistical Analyses
For analyses of risk factors for KSHV shedders we excluded individuals who were KSHV seronegative, who did not have oral uids tested for KSHV DNA by qPCR, or who were under three years of age due to di culties with collecting valid mouthwash samples from younger children.Descriptive statistics were used to describe individuals included in nal analyses.Generalized linear mixed logistic regression model with a speci ed binomial distribution and included logit link function were used to model risk factors for being an ever vs never shedder and among shedders with 2 + visits, of being an always vs intermittent shedder using PROC GLIMMIX in SAS.Models included a random intercept and random slope for household effects.To model risk factors for increased levels of KSHV viral loads among shedders, we applied linear mixed effects models including a random intercept and random slope for individual effects and an unstructured covariance structure.Type III tests of xed effects were used to identify if trends were statistically signi cant.Confounding variables identi ed a priori were included in adjusted analyses if they were associated with both the exposure and outcome by p < 0.02 and changed the crude estimate by 10+%.If no variables met these criteria, then crude estimates were reported.To determine the amount of total variation in the probability of being an ever vs never KSHV shedder, and among KSHV shedders of being an always vs intermittent shedder that is accounted for by household we calculated the intraclass correlation coe cient (ICC) (25).P-values < 0.05 considered statistically signi cant.Models of risk factors were completed using SAS 9.4 [SAS Institute In, Cary, NC].

Geospatial Analysis
Descriptive maps and spatial analyses were completed in R version 4.3.3.Hot-spot analyses generating local Getis-Ord G i *statistics using 'spdep' R package (26-29) were performed to detect statistically signi cant clusters of high and low feature values within the study area, which are unlikely the result of random chance.Inverse distance weighted (IDW), deterministic spatial interpolation methods were performed using the 'gstat' R package (30) to visualize feature hot and cold spot distribution (29).Hotspot analysis results are presented as a Gi* statistic, which is represented as a Z-score, where higher values signify a larger clustering intensity, while the (positive or negative) direction indicate high or low value clusters, respectively.An associated p-value indicating statistically signi cant results is also provided.R code is available on github repository (31).

Participant inclusion
We enrolled 469 participants of all ages from 90 households.Of those we excluded 129 (28%) individuals who either had no KSHV serology results (n = 28, 6%), were KSHV seronegative (n = 75, 16%), did not have oral uids tested for KSHV DNA by qPCR (n = 22, 5%), or were under three years of age due to di culties with collecting valid mouthwash samples from younger children (n = 4, < 1%).The majority (n = 56, 75%) of those who were KSHV seronegative were under 10 years of age.This resulted in the inclusion of 340 KSHV seropositive participants from 89 households.We con rmed the status of at least one PLWH in 40 of the included households (positive household HIV status), leaving 49 households de ned as having no PLWH.

Household and participant characteristics
Household member size ranged from 1 to 16, with an average of 5.2 (standard deviation: 2.9) individuals per home.In one household, consisting of two members only, no KSHV seropositive individuals were identi ed, despite the high sensitivity of the multiplex assay.Of the 89 households included in our analysis, the number of KSHV seropositive members ranged from 1 to 14 with an average of 4.2 (2.7) per home.The proportion of KSHV seropositive members ranged from 0.2 to 1.0 per home with an average of 0.8(0.2).
Of the 340 KSHV seropositive participants included in our nal analyses, 25 (7%) completed one visit, 57 (17%) two visits, and 258 (76%) completed all three visits.Half of participants were female (54%), and half were children under 14 years of age (49%).Of included participants, 14% were PLWH, while HIV serostatus was missing for 27%.Among individuals who self-reported an HIV infection, all stated they were currently on ART and a median of seven years had passed from initial HIV diagnosis.Nearly all participants were classi ed as EBV seropositive.
Participants from households with at least one PLWH compared to households with none were more likely to be over 40 years of age (30% vs 14%), and more often classi ed into the fourth or higher SES quintile (68% vs 29%).Fewer individuals from households with a PLWH reported being sick at the time of visit compared to households with no PLWH (8% vs 26%) [Table 1].All variables missing < 2% data except where speci ed.
HIV seropositive individuals were those who self-reported as HIV positive or whose HIV status was con rmed using previously collected GPC census or other study data.
Years since HIV diagnosis and ART status were available for those who self-reported their HIV status (n = 39).
EBV seropositivity was de ned as detection of anti-EBV antibodies to VCA or EBNA-1.
Approximately 19% (ICC = 0.191) of variability in shedding was accounted for by households in the study while 81% of the variability in shedding was accounted for by individual or other factors outside of the household.There was a statistically signi cant amount of variability in the log odds of being an ever shedder between the households in our sample [00 = .7746;p = 0.010].Higher odds of shedding were statistically signi cantly associated with an increasing number of KSHV seropositive household members (Odds ratio (OR): 1.14 (95% Con dence interval, CI: All variables missing < 2% data except where speci ed.
HIV seropositive individuals were those who self-reported as HIV positive or whose HIV status was con rmed using previously collected GPC census or other study data.
Years since HIV diagnosis and ART status were available for those who self-reported their HIV status (n = 39).
EBV seropositivity was de ned as detection of anti-EBV IgG antibodies to VCA or EBNA-1.
All models included a random intercept and random slope for household.
EBV seropositivity was de ned as detection of anti-EBV IgG antibodies to VCA or EBNA-1.
All models included a random intercept and random slope for household.
a Adjusted for age (categorical) [Table 3 Here]

KSHV viral load in oral uids
We found a similar statistically signi cant trend in KSHV viral loads based on age, with higher average KSHV viral loads identi ed in 10-19-year-olds, after adjustment for number of household members and household HIV status (Type III p = 0.027).On average, higher KSHV viral loads were identi ed in individuals living with more household members [coe cient = 0.06, 95% con dence interval (95%CI):0.01,0.02,p = 0.042] and living with more KSHV seropositive household members after adjustment for household HIV status [coe cient = 0.08, 95%CI:0.01,0.15;p= 0.021], and among those living in a household with at least one PLWH, after adjustment for number of household members [coe cient = 0.51, 95%CI:0.04,0.98,p = 0.033].KSHV viral loads in oral uids were also higher on average in always vs intermittent shedders [coe cient = 1.62, 95%CI:1.19,2.05;p < 0.001] and with increasing number of samples with KSHV DNA detected [Table 4].When restricted to individuals with all three visits, the direction and magnitude of the association of increasing number of samples with KSHV DNA detected and KSHV viral loads did not change.All models included a random intercept and random slope for household.
a Adjusted for Age (categorical) b Adjusted for number household members c Adjusted for household HIV status (any vs none) [Table 4 Here] Descriptive maps and hot spot provide a geospatial distribution of households by size, HIV and KSHV serostatus, and KSHV shedding status in Fig. 1.Cluster analyses identi ed larger household sizes in the west and in the center and coldspots of lower household size in the north of the region.These hotspots were similar to the location of hotspots of KSHV seropositive individuals per household found in the west and center but no statistically signi cant coldspots of KSHV seropositivity were identi ed.Households with higher numbers of PLWH were identi ed in the southeast while those with lower numbers of PLWH and with higher numbers of KSHV seropositive individuals were identi ed in the west.There was no spatial overlap of hotspots of PLWH per household with hotspots of KSHV seropositive individuals per household.
Five statistically signi cant hotspots of higher numbers of KSHV shedders per household were located in the west of the GPC and these overlapped spatially with three households that were statistically signi cant hotspots for both larger household size and higher number of KSHV seropositive individuals per household.Approximately two hotspot locations of KSHV seropositive individuals and KSHV shedders overlapped spatially with two statistically signi cant cold spots of individuals with HIV per household.No statistically signi cant cold spots of lower numbers of KHSV shedders per household were detected.Among households with at least one KSHV shedder, statistically signi cant hotspots of higher numbers of always shedders clustered in the middle of the region, while no coldspots were identi ed [Figure 2].

Discussion
In this longitudinal study of rural Uganda households, we found that living with at least one PLWH, though not associated with the probability of KSHV shedding, was associated with higher KSHV viral loads among KSHV shedders.The number KSHV seropositive residents in a household was associated with KSHV shedding and with increased viral loads among shedders.We also identi ed a moderate variability in being a KSHV ever shedder that can be accounted for at the household level.In addition, both KSHV shedding frequency and viral loads in the oral uids appeared to be age dependent, and individuals with more frequent shedding had higher viral loads.
The variability in being an ever shedder accounted for by household was moderate, at 19%.This variability, as measured by intraclass correlation analysis, likely stems from household-related factors that promote KSHV reactivation in the oral cavity.Our work in another Ugandan cohort identi ed higher KSHV viral loads in the oral uids of children with helminthiasis and an inverse association between KSHV shedding and anti-malaria antibody levels (32), suggesting that co-infections, which may be common within a household, may play a role in oral KSHV reactivation.Prior studies in this cohort and in a pediatric sickle cell study, however, found no associations between oral KSHV shedding and parasitic infections, including malaria (4,33).Unfortunately, our study lacked data on individual infections, precluding adjustment for these factors.
We did nd a statistically signi cant association between the number of KSHV seropositive household members and the probability of ever shedding KSHV.Previous studies in Zambia reported an elevated risk of KSHV infection in children with increasing number of KSHV seropositive household members (34) but did not examine the likelihood of KSHV shedding among those already seropositive.However, we also found an effect of household size in general.These ndings suggest that while household-speci c factors may contribute to KSHV shedding, individual-level factors primarily drive oral KSHV reactivation and shedding probability.
Among KSHV shedders, we observed a statistically signi cant age-related trend, with individuals aged 10-19 being more likely to be always shedders, with higher viral loads.These ndings align with previous reports from Uganda, indicating age-dependent variations in KSHV shedding dynamics.Speci cally, that KSHV viral loads in oral uids were highest in 6-12-year-old shedders decreasing with age afterwards (33) decreasing with age afterwards and that detection of KSHV DNA was twice as likely in children compared to their mothers (32).These studies also reported a higher likelihood of KSHV shedding and higher viral loads in males (32,33) though we did not nd this same association by sex.Nevertheless, our ndings underscore the signi cance of age in ongoing KSHV transmission, particularly the possible contribution of children within households.
Among KSHV shedders, individuals living with at least one PLWH exhibited higher viral loads.
Previous studies have reported higher KSHV seropositivity among children of women living with HIV/AIDS (WLHA) (35)(36)(37), potentially indicative of a role of HIV infection in promoting reactivation of KSHV in the oral cavity and supporting transmission within a household.We did not however identify associations between individual HIV status and likelihood of KSHV shedding or viral loads.Inconsistent results have been reported regarding the effect of HIV infection on KSHV shedding (5-9, 14, 38) though most previous longitudinal studies reported no relation between KSHV shedding and HIV status (1, 10-13, 17, 39, 40).Among KSHV shedders, the association between HIV infection and KHSV viral loads in PLWH have also been inconsistently observed (1,6,10,14) suggesting a complex interaction may exist between HIV and oral KSHV reactivation.
Additionally, we found that KSHV viral loads were higher among individuals who consistently shed the virus compared to those who shed intermittently, with viral loads increasing with the frequency of shedding episodes.This corroborates ndings from previous studies in Kenya and an analysis across multiple regions including the US, Peru, Cameroon, Uganda, and Kenya, which indicated a positive correlation between shedding frequency and viral load levels (11,12).These ndings are also supported by a study in North America reporting that past shedding predicted future shedding occurrences and corresponding viral load levels in saliva (41).The factors in uencing shedding frequency and their predictive value for viral loads require additional study.
Our geospatial analysis revealed overlapping hotspots of KSHV seropositivity and shedding within households, particularly in the western region of the study area.These hotspots differed from hotspots of HIV infection.The correspondence between hotspots of KSHV seropositivity and shedding with hotspots of larger household size in the west suggests an association between KSHV seropositivity and shedding and proximity to larger household size in increased housing density settings.The number of individuals per household tended to be low in the north and was con rmed by hotspot analyses, revealing statistically signi cant coldspots of household size.Therefore, statistically signi cant spatial clusters were not expected in this region.Among households with at least one KSHV shedder we did see clustering of hotspots towards the center of the region which differed from those identi ed for shedding.

Table 1
Characteristics of KSHV Seropositive Participants by Household HIV Status 1.03-1.26;p = 0.013) and with an increasing number of household members in general (OR: 1.10, (95% CI, 1.00,1.21;p = 0.051).There were no other statistically signi cant risk factors for KSHV shedding at the individual or the household level including the individual's HIV infection [Table 2].